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A possible link between chemotherapy and cognitive impairment has been identified. In the literature, this condition is usually called chemobrain and can mostly affect some memory domain but can lead also to other cognitive impairments. Olfaction, which is known to be linked with cognitive domain and the nociception system, can also be affected by chemotherapy. The aim of this study was to investigate the main cognitive and olfactory abilities and the functional and nutritional state of a cohort of chemotherapy and immunotherapy onco-geriatric patients and control geriatrics subjects. Cognitive, olfactory, geriatric and nutritional assessments were performed through the Mini Mental State Examination (MMSE), Sniffin' Sticks Screening 12, G8 test and a questionnaire on the adherence of the Mediterranean diet, respectively. Our findings show a gender effect on the MMSE. Overall results indicate more pronounced impairments both at the cognitive and frailty level regardless of the type of therapy. On the other hand, the Sniffin' Sticks performances highlight a significant decrease in olfactory perception ability of subjects following immunotherapy. Significant correlations between olfactory performance and MMSE and G8 scores were also found, as well as between MMSE and G8 measures.

Many studies have focused on navigation, spatial skills, and the olfactory system in comparative models, including those concerning the relationship between them and physical activity. Although the results are often in contrast with each other, it is assumed that physical activity can affect cognition in different ways-both indirectly and through a certain influence on some brain structures. In contrast, there is little research that focuses on the relationship between spatial abilities and olfactory abilities in humans. This research aimed to evaluate and compare the performance in working memory tasks of athletes and non-athletes who require good visual-spatial navigation, olfactory-spatial navigation, and olfactory-semantic skills. The study involved 236 participants (83 athletes) between the ages of 18 and 40. All subjects were matched by age or sex. The standard Corsi Block Tapping Test (CBTT) was administrated to investigate the visual-spatial memory. Olfactory-spatial navigation and olfactory-semantic skills were assessed with two modified versions of CBTT: Olfactory CBTT (OCBTT) and Semantic-Olfactory CBTT (SOCBTT) respectively. The results show differences between the CORSI conditions in direction of a poor performance for athletes. A gender effect in favor of men was also found, particularly in the classic version of the CBTT. Both groups performed better in the classic version of the CBTT than OCBTT and SOCBTT. The mean of SOCBTT results is markedly lower, perhaps due to the different information processing systems needed to perform this kind of task. It is possible to explain how sports practice can affect tasks that require spatial skills and olfactory perception differently, thus supporting new hypotheses and opening new scientific horizons., Competing Interests: The authors declare no conflict of interest.

Background: Keratoconus is a disorder characterized by progressive thinning and distortion of the cornea. If detected at an early stage, corneal collagen cross-linking can prevent disease progression and further visual loss. Although advanced forms are easily detected, reliable identification of subclinical disease can be problematic. Several different machine learning algorithms have been used to improve the detection of subclinical keratoconus based on the analysis of multiple types of clinical measures, such as corneal imaging, aberrometry, or biomechanical measurements., Objective: The aim of this study is to survey and critically evaluate the literature on the algorithmic detection of subclinical keratoconus and equivalent definitions., Methods: For this systematic review, we performed a structured search of the following databases: MEDLINE, Embase, and Web of Science and Cochrane Library from January 1, 2010, to October 31, 2020. We included all full-text studies that have used algorithms for the detection of subclinical keratoconus and excluded studies that did not perform validation. This systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations., Results: We compared the measured parameters and the design of the machine learning algorithms reported in 26 papers that met the inclusion criteria. All salient information required for detailed comparison, including diagnostic criteria, demographic data, sample size, acquisition system, validation details, parameter inputs, machine learning algorithm, and key results are reported in this study., Conclusions: Machine learning has the potential to improve the detection of subclinical keratoconus or early keratoconus in routine ophthalmic practice. Currently, there is no consensus regarding the corneal parameters that should be included for assessment and the optimal design for the machine learning algorithm. We have identified avenues for further research to improve early detection and stratification of patients for early treatment to prevent disease progression., (©Howard Maile, Ji-Peng Olivia Li, Daniel Gore, Marcello Leucci, Padraig Mulholland, Scott Hau, Anita Szabo, Ismail Moghul, Konstantinos Balaskas, Kaoru Fujinami, Pirro Hysi, Alice Davidson, Petra Liskova, Alison Hardcastle, Stephen Tuft, Nikolas Pontikos. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 13.12.2021.)